{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "aqZ7F-q5A6lc"
   },
   "outputs": [],
   "source": [
    "import torch as t\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import math"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### build network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "CJs2QCkA9umU"
   },
   "outputs": [],
   "source": [
    "def channel_shuffle(x, groups=2):\n",
    "  bat_size, channels, w, h = x.shape\n",
    "  group_c = channels // groups\n",
    "  x = x.view(bat_size, groups, group_c, w, h)\n",
    "  x = t.transpose(x, 1, 2).contiguous()\n",
    "  x = x.view(bat_size, -1, w, h)\n",
    "  return x\n",
    "\n",
    "# used in the block\n",
    "def conv_1x1_bn(in_c, out_c, stride=1):\n",
    "  return nn.Sequential(\n",
    "    nn.Conv2d(in_c, out_c, 1, stride, 0, bias=False),\n",
    "    nn.BatchNorm2d(out_c),\n",
    "    nn.ReLU(True)\n",
    "  )\n",
    "\n",
    "def conv_bn(in_c, out_c, stride=2):\n",
    "  return nn.Sequential(\n",
    "    nn.Conv2d(in_c, out_c, 3, stride, 1, bias=False),\n",
    "    nn.BatchNorm2d(out_c),\n",
    "    nn.ReLU(True)\n",
    "  )\n",
    "\n",
    "\n",
    "class ShuffleBlock(nn.Module):\n",
    "  def __init__(self, in_c, out_c, downsample=False):\n",
    "    super(ShuffleBlock, self).__init__()\n",
    "    self.downsample = downsample\n",
    "    half_c = out_c // 2\n",
    "    if downsample:\n",
    "      self.branch1 = nn.Sequential(\n",
    "          # 3*3 dw conv, stride = 2\n",
    "          nn.Conv2d(in_c, in_c, 3, 2, 1, groups=in_c, bias=False),\n",
    "          nn.BatchNorm2d(in_c),\n",
    "          # 1*1 pw conv\n",
    "          nn.Conv2d(in_c, half_c, 1, 1, 0, bias=False),\n",
    "          nn.BatchNorm2d(half_c),\n",
    "          nn.ReLU(True)\n",
    "      )\n",
    "      \n",
    "      self.branch2 = nn.Sequential(\n",
    "          # 1*1 pw conv\n",
    "          nn.Conv2d(in_c, half_c, 1, 1, 0, bias=False),\n",
    "          nn.BatchNorm2d(half_c),\n",
    "          nn.ReLU(True),\n",
    "          # 3*3 dw conv, stride = 2\n",
    "          nn.Conv2d(half_c, half_c, 3, 2, 1, groups=half_c, bias=False),\n",
    "          nn.BatchNorm2d(half_c),\n",
    "          # 1*1 pw conv\n",
    "          nn.Conv2d(half_c, half_c, 1, 1, 0, bias=False),\n",
    "          nn.BatchNorm2d(half_c),\n",
    "          nn.ReLU(True)\n",
    "      )\n",
    "    else:\n",
    "      # in_c = out_c\n",
    "      assert in_c == out_c\n",
    "        \n",
    "      self.branch2 = nn.Sequential(\n",
    "          # 1*1 pw conv\n",
    "          nn.Conv2d(half_c, half_c, 1, 1, 0, bias=False),\n",
    "          nn.BatchNorm2d(half_c),\n",
    "          nn.ReLU(True),\n",
    "          # 3*3 dw conv, stride = 1\n",
    "          nn.Conv2d(half_c, half_c, 3, 1, 1, groups=half_c, bias=False),\n",
    "          nn.BatchNorm2d(half_c),\n",
    "          # 1*1 pw conv\n",
    "          nn.Conv2d(half_c, half_c, 1, 1, 0, bias=False),\n",
    "          nn.BatchNorm2d(half_c),\n",
    "          nn.ReLU(True)\n",
    "      )\n",
    "      \n",
    "      \n",
    "  def forward(self, x):\n",
    "    out = None\n",
    "    if self.downsample:\n",
    "      # if it is downsampling, we don't need to do channel split\n",
    "      out = t.cat((self.branch1(x), self.branch2(x)), 1)\n",
    "    else:\n",
    "      # channel split\n",
    "      channels = x.shape[1]\n",
    "      c = channels // 2\n",
    "      x1 = x[:, :c, :, :]\n",
    "      x2 = x[:, c:, :, :]\n",
    "      out = t.cat((x1, self.branch2(x2)), 1)\n",
    "    return channel_shuffle(out, 2)\n",
    "    \n",
    "\n",
    "class ShuffleNet2(nn.Module):\n",
    "  def __init__(self, num_classes=2, input_size=224, net_type=1):\n",
    "    super(ShuffleNet2, self).__init__()\n",
    "    assert input_size % 32 == 0 # 因为一共会下采样32倍\n",
    "    \n",
    "    \n",
    "    self.stage_repeat_num = [4, 8, 4]\n",
    "    if net_type == 0.5:\n",
    "      self.out_channels = [3, 24, 48, 96, 192, 1024]\n",
    "    elif net_type == 1:\n",
    "      self.out_channels = [3, 24, 116, 232, 464, 1024]\n",
    "    elif net_type == 1.5:\n",
    "      self.out_channels = [3, 24, 176, 352, 704, 1024]\n",
    "    elif net_type == 2:\n",
    "      self.out_channels = [3, 24, 244, 488, 976, 2948]\n",
    "    else:\n",
    "      print(\"the type is error, you should choose 0.5, 1, 1.5 or 2\")\n",
    "      \n",
    "    # let's start building layers\n",
    "    self.conv1 = nn.Conv2d(3, self.out_channels[1], 3, 2, 1)\n",
    "    self.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1)\n",
    "    in_c = self.out_channels[1]\n",
    "    \n",
    "    self.stages = []\n",
    "    for stage_idx in range(len(self.stage_repeat_num)):\n",
    "      out_c = self.out_channels[2+stage_idx]\n",
    "      repeat_num = self.stage_repeat_num[stage_idx]\n",
    "      for i in range(repeat_num):\n",
    "        if i == 0:\n",
    "          self.stages.append(ShuffleBlock(in_c, out_c, downsample=True))\n",
    "        else:\n",
    "          self.stages.append(ShuffleBlock(in_c, in_c, downsample=False))\n",
    "        in_c = out_c\n",
    "    self.stages = nn.Sequential(*self.stages)\n",
    "    \n",
    "    in_c = self.out_channels[-2]\n",
    "    out_c = self.out_channels[-1]\n",
    "    self.conv5 = conv_1x1_bn(in_c, out_c, 1)\n",
    "    self.g_avg_pool = nn.AvgPool2d(kernel_size=(int)(input_size/32)) # 如果输入的是224，则此处为7\n",
    "    \n",
    "    # fc layer\n",
    "    self.fc = nn.Linear(out_c, num_classes)\n",
    "    \n",
    "\n",
    "  def forward(self, x):\n",
    "    x = self.conv1(x)\n",
    "    x = self.maxpool(x)\n",
    "    x = self.stages(x)\n",
    "    x = self.conv5(x)\n",
    "    x = self.g_avg_pool(x)\n",
    "    x = x.view(-1, self.out_channels[-1])\n",
    "    x = self.fc(x)\n",
    "    return x\n",
    "    \n",
    "    \n",
    "  \n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "T3FNodcmwtS3"
   },
   "outputs": [],
   "source": [
    "model = ShuffleNet2()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "YEAIPfRpKQyA"
   },
   "outputs": [],
   "source": [
    "device = t.device(\"cuda\" if t.cuda.is_available() else \"cpu\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "w1i1wZ7QNMR_"
   },
   "outputs": [],
   "source": [
    "model = model.to(device)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Process data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> You can modify this part to train on your own data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The train data format"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The test data format"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "rjkcnAy4NpfS"
   },
   "outputs": [],
   "source": [
    "from torchvision import datasets, transforms\n",
    "import os\n",
    "import time\n",
    "from torch.utils import data\n",
    "import numpy as np\n",
    "from PIL import Image\n",
    "import copy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "dbQDdP5AZgSU"
   },
   "source": [
    "[How to process data using Dataset, Dataloader](https://zhuanlan.zhihu.com/p/30934236)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "n4so3YlQY5dx"
   },
   "outputs": [],
   "source": [
    "class DogCat(data.Dataset):\n",
    "  def __init__(self, root, trans=None, train=True, test=False):\n",
    "    self.test = test\n",
    "    self.train = train\n",
    "    imgs = [os.path.join(root, img) for img in os.listdir(root)]\n",
    "    '''\n",
    "    the format of test and trian image name is different\n",
    "    as for test: /test/102.jpg\n",
    "    as for train: /train/cat.1.jpg\n",
    "    '''\n",
    "    if test: # root: './dogvscat/test/' imgs = [\"xx/123.jpg\", \"xx/234.jpg\", ...]\n",
    "      sorted(imgs, key=lambda x: int(x.split(\".\")[-2].split(\"/\")[-1])) \n",
    "    else:\n",
    "      sorted(imgs, key=lambda x: int(x.split(\".\")[-2])) \n",
    "    \n",
    "    # shuffle\n",
    "    np.random.seed(100)\n",
    "    imgs = np.random.permutation(imgs)\n",
    "    \n",
    "    # split dataset\n",
    "    if self.test:\n",
    "      self.imgs = imgs\n",
    "    elif train:\n",
    "      self.imgs = imgs[:int(0.7*len(imgs))]\n",
    "    else:\n",
    "      self.imgs = imgs[int(0.7*len(imgs)):]\n",
    "    \n",
    "    if trans==None:\n",
    "      normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],\n",
    "                                        std=[0.229, 0.224, 0.225])\n",
    "      # test and dev dataset do not need to do data augemetation\n",
    "      if self.test or not self.train:\n",
    "        self.trans = transforms.Compose([\n",
    "                                        transforms.Resize(224),\n",
    "                                        transforms.CenterCrop(224),\n",
    "                                        transforms.ToTensor(),\n",
    "                                        normalize\n",
    "                                        ])\n",
    "      else:\n",
    "        self.trans = transforms.Compose([\n",
    "                                        transforms.Resize(256),\n",
    "                                        transforms.CenterCrop(224), # RandomSizedCrop(224)??\n",
    "                                        transforms.RandomHorizontalFlip(),\n",
    "                                        transforms.ToTensor(),\n",
    "                                        normalize\n",
    "                                        ])\n",
    "      \n",
    " \n",
    "  def __getitem__(self, index):\n",
    "    '''\n",
    "    as for test: just return the id of picture.\n",
    "    as for train and dev: return 1 if dog, return 0 if cat\n",
    "    '''\n",
    "    imgpath = self.imgs[index]\n",
    "    if self.test:\n",
    "      label = int(imgpath.split(\".\")[-2].split(\"/\")[-1])\n",
    "    else:\n",
    "      kind = imgpath.split(\".\")[-3].split(\"/\")[-1]\n",
    "      label = 1 if kind == \"dog\" else 0\n",
    "    img = Image.open(imgpath)\n",
    "    img = self.trans(img)\n",
    "    return img, label\n",
    "  \n",
    "  def __len__(self):\n",
    "    return len(self.imgs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "-Ato2LZhnZQC"
   },
   "outputs": [],
   "source": [
    "train_dataset = DogCat(\"./dogvscat/train\", train=True)\n",
    "val_dataset = DogCat(\"./dogvscat/train\", train=False, test=False)\n",
    "train_loader = data.DataLoader(train_dataset,\n",
    "                               batch_size = 32,\n",
    "                               shuffle=True\n",
    "                               )\n",
    "val_loader = data.DataLoader(val_dataset,\n",
    "                             batch_size = 32,\n",
    "                             shuffle=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "BNprrppqooYO"
   },
   "outputs": [],
   "source": [
    "dataloader = {}\n",
    "dataloader[\"train\"] = train_loader\n",
    "dataloader[\"val\"] = val_loader"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### training and validating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "sBlZLgcyPTGd"
   },
   "outputs": [],
   "source": [
    "device = t.device(\"cuda\" if t.cuda.is_available() else \"cpu\")\n",
    "model = ShuffleNet2()\n",
    "model = model.to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "5_YYFannPi3Z"
   },
   "outputs": [],
   "source": [
    "loss_fn = nn.CrossEntropyLoss()\n",
    "optimizer = t.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "4rr_xnFcN0WV"
   },
   "outputs": [],
   "source": [
    "def train_model(model, dataloaders, loss_fn, optimizer, num_epochs=5):\n",
    "    best_model_wts = copy.deepcopy(model.state_dict())\n",
    "    best_acc = 0.\n",
    "    val_acc_history = []\n",
    "    for epoch in range(num_epochs):\n",
    "        for phase in [\"train\", \"val\"]:\n",
    "            running_loss = 0.\n",
    "            running_corrects = 0.\n",
    "            if phase == \"train\":\n",
    "                model.train()\n",
    "            else:\n",
    "                model.eval()\n",
    "                \n",
    "            for inputs, labels in dataloaders[phase]:\n",
    "                inputs, labels = inputs.to(device), labels.to(device)\n",
    "                \n",
    "                with t.autograd.set_grad_enabled(phase==\"train\"):\n",
    "                    outputs = model(inputs) # bsize * 2 , because it is a binary classification\n",
    "                    loss = loss_fn(outputs, labels) \n",
    "                \n",
    "                preds = outputs.argmax(dim=1)\n",
    "                if phase == \"train\":\n",
    "                    optimizer.zero_grad()\n",
    "                    loss.backward()\n",
    "                    optimizer.step()\n",
    "                running_loss += loss.item() * inputs.size(0)\n",
    "                running_corrects += t.sum(preds.view(-1) == labels.view(-1)).item()\n",
    "                \n",
    "            epoch_loss = running_loss / len(dataloaders[phase].dataset)\n",
    "            epoch_acc = running_corrects / len(dataloaders[phase].dataset)\n",
    "            \n",
    "            print(\"Phase {} loss: {}, acc: {}\".format(phase, epoch_loss, epoch_acc))\n",
    "            \n",
    "            if phase == \"val\" and epoch_acc > best_acc:\n",
    "                best_acc = epoch_acc\n",
    "                best_model_wts = copy.deepcopy(model.state_dict())\n",
    "            if phase == \"val\":\n",
    "                val_acc_history.append(epoch_acc)\n",
    "    model.load_state_dict(best_model_wts)    \n",
    "    return model, val_acc_history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "ASB6f6Ayabbo"
   },
   "outputs": [],
   "source": [
    "model, val_logs = train_model(model, dataloader, loss_fn, optimizer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### save the best model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "torch.save(model.state_dict(), \"./save/\" + str(int(time.time()))+'.pkl')"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "shufflenet2",
   "provenance": [],
   "version": "0.3.2"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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